I have 8 multilevel logistic regression brms models fit to the same data. Each model is relatively large, e.g., the file sizes of saved models are approx 1GB-1.5GB. Comparing all 8 using
waic takes about 10 minutes, but comparing them using
loo seems like it will take many many hours. I can’t say for sure because after about 6 hours or so the comparison lead to all the RAM being used (250GB).
I presume I can solve the RAM problem by
pointwise=TRUE, but that will entail the comparison will take even longer.
I am working on 36 core machine, but
loo is only using one core (adding
cores = 2 or any other number as an argument to
loo does nothing).
I presume there is no in principle reason why the model comparison can not be done in parallel, so is there any way of making this happen? I presume I could just use R’s
parallel commands, like
parLapply etc, to do all 28 pairwise comparison. That’s fine, and I will try that, but I was wondering if I am missing something simple and easy.
- Operating System: Linux (Ubuntu 18.04)
- brms Version: 2.4.0